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Data analysis
Research Aptitude
Useful for: OSSC Art Education Instructor, OSSC Economics, OSSC English, OSSC Foundation Course, OSSC Geography, OSSC History, OSSC Mathematics, OSSC Odia
Overview
Data analysis turns raw data into findings — statistics for quantitative data and coding for qualitative data.
Key points
- Descriptive statistics: mean, median, mode, standard deviation.
- The t-test compares two means; ANOVA compares three or more.
- Chi-square tests association between categorical variables.
- Correlation measures the strength of a relationship (−1 to +1).
- Parametric tests assume normal distribution and interval/ratio data; non-parametric tests do not.
- Qualitative analysis codes data into categories and themes.
Explanation
- Choose tests by data scale and design.
- Report effect sizes along with p-values.
- Software helps but interpretation is the researcher’s job.
- Outliers need careful handling.
- Present results in clear tables and graphs.
Step by step
- Identify the concept, method or policy asked.
- Recall the definition, thinker, year or rule.
- Apply it to the situation and eliminate extreme options.
Examples
- Comparing mean scores of two classes → t-test.
- Relationship between gender and stream choice (categories) → chi-square.
- Comparing three teaching methods → ANOVA.
Traps and advanced points
- Trap: Using a t-test for three groups.
- Trap: Parametric tests on ordinal data.
- Trap: Only p-values without effect size.
Quick revision
- t-test 2 groups; ANOVA 3+.
- Chi-square for categories.
- Parametric vs non-parametric.
Practice MCQs
Data collected first-hand by the researcher are —
- secondary data
- primary data
- tertiary data
- meta-data
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Answer: (b) primary data. Surveys, interviews and experiments give primary data.
A researcher uses Census figures published by the government. These are —
- primary data
- secondary data
- experimental data
- raw observations
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Answer: (b) secondary data. Data collected by someone else are secondary.
To compare the means of two groups, use a —
- chi-square
- ANOVA
- correlation only
- t-test
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Answer: (d) t-test. t-test for two groups.
To compare three or more group means, use —
- t-test
- ANOVA
- chi-square
- median test only
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Answer: (b) ANOVA. Analysis of variance.
Association between two categorical variables is tested by —
- regression only
- chi-square
- t-test
- ANOVA
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Answer: (b) chi-square. Chi-square for categories.
Correlation values range from —
- 0 to 1
- −1 to +1
- 0 to 100
- −10 to +10
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Answer: (b) −1 to +1. Perfect negative to perfect positive.
Parametric tests assume —
- nominal data only
- no assumptions
- small samples only
- normal distribution and interval/ratio data
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Answer: (d) normal distribution and interval/ratio data. Non-parametric tests relax these.
Effect size shows —
- the magnitude of a difference
- the sample size
- the p-value only
- the title
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Answer: (a) the magnitude of a difference. Practical importance.
Qualitative data analysis mainly involves —
- coding into themes
- t-tests
- ANOVA
- chi-square
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Answer: (a) coding into themes. Codes grouped into themes.
Mean, median and standard deviation are —
- sampling methods
- descriptive statistics
- inferential tests
- qualitative codes
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Answer: (b) descriptive statistics. They summarise data.
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